Efficient decentralized coordination of large-scale plug-in electric vehicle charging

Zhongjing Ma, Suli Zou, Long Ran, Xingyu Shi, Ian A. Hiskens

Research output: Contribution to journalArticlepeer-review

119 Citations (Scopus)

Abstract

Minimizing the grid impacts of large-scale plug-in electric vehicle (PEV) charging tends to be associated with coordination strategies that seek to fill the overnight valley in electricity demand. However such strategies can result in high charging power, raising the possibility of local overloads within the distribution grid and of accelerated battery degradation. The paper establishes a framework for PEV charging coordination that facilitates the tradeoff between total generation cost and the local costs associated with overloading and battery degradation. A decentralized approach to solving the resulting large-scale optimization problem involves each PEV minimizing their charging cost with respect to a forecast price profile while taking into account local grid and battery effects. The charging strategies proposed by participating PEVs are used to update the price profile which is subsequently rebroadcast to the PEVs. The process then repeats. It is shown that under mild conditions this iterative process converges to the unique, efficient (socially optimal) coordination strategy.

Original languageEnglish
Pages (from-to)35-47
Number of pages13
JournalAutomatica
Volume69
DOIs
Publication statusPublished - Jul 2016

Keywords

  • Battery degradation
  • Decentralized optimization
  • Distribution grid management
  • Efficient power system operation
  • Load control
  • Plug-in electric vehicles (PEVs)

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